The dataset viewer is not available for this dataset.
Error code: ConfigNamesError
Exception: TypeError
Message: SplitInfo.__init__() got an unexpected keyword argument 'download_size'
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/dataset/config_names.py", line 66, in compute_config_names_response
config_names = get_dataset_config_names(
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 161, in get_dataset_config_names
dataset_module = dataset_module_factory(
^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/load.py", line 1029, in dataset_module_factory
raise e1 from None
File "/usr/local/lib/python3.12/site-packages/datasets/load.py", line 1004, in dataset_module_factory
).get_module()
^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/load.py", line 604, in get_module
dataset_infos = DatasetInfosDict.from_dataset_card_data(dataset_card_data)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/info.py", line 386, in from_dataset_card_data
dataset_info = DatasetInfo._from_yaml_dict(dataset_card_data["dataset_info"])
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/info.py", line 319, in _from_yaml_dict
yaml_data["splits"] = SplitDict._from_yaml_list(yaml_data["splits"])
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/splits.py", line 600, in _from_yaml_list
return cls.from_split_dict(yaml_data)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/splits.py", line 570, in from_split_dict
split_info = SplitInfo(**split_info)
^^^^^^^^^^^^^^^^^^^^^^^
TypeError: SplitInfo.__init__() got an unexpected keyword argument 'download_size'Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
Perfect Blend - Qwen3-8B Regenerated
Dataset Description
This dataset is a regenerated version of the Open Perfect Blend (Perfect Blend) data. Each conversation was re-generated by Qwen/Qwen3-8B as the target model, so that the responses follow the target model's output distribution. It is intended for training speculative decoding draft models (e.g., DFlash, EAGLE) that align with Qwen3-8B, such as in SpecForge.
- Target model: Qwen/Qwen3-8B
- Source: Perfect Blend (mlabonne/open-perfectblend)
- Splits:
train(1.42M rows) - Approximate size: ~20.4 GB (Parquet)
Data Structure
| Column | Type | Description |
|---|---|---|
id |
int64 | Sample index |
conversations |
list | List of turns with role, content, thinking |
status |
string | e.g. "success" for successful regeneration |
Each item in conversations has:
role:"user"or"assistant"content: text of the messagethinking: optional thinking content (e.g. for reasoning models)
How to Load / Download
Using the datasets library
from datasets import load_dataset
# Load the full dataset
dataset = load_dataset("jihwan1205/perfectblend-qwen3-8b-regen", split="train")
# With streaming to avoid loading everything into memory
dataset = load_dataset(
"jihwan1205/perfectblend-qwen3-8b-regen",
split="train",
streaming=True
)
Using in SpecForge (e.g. DFlash online training)
Use this dataset as the training data path:
--train-data-path jihwan1205/perfectblend-qwen3-8b-regen
License
Same as the source dataset Open Perfect Blend. Please check the original dataset page for license details.
Citation
If you use this dataset, please cite the original Perfect Blend and the model used for regeneration (Qwen3-8B).
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